{"pageNumber":"1244","pageRowStart":"31075","pageSize":"25","recordCount":165296,"records":[{"id":70124494,"text":"70124494 - 2015 - Spatiotemporal variation of surface shortwave forcing from fire-induced albedo change in interior Alaska","interactions":[],"lastModifiedDate":"2017-01-18T10:10:24","indexId":"70124494","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1170,"text":"Canadian Journal of Forest Research","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal variation of surface shortwave forcing from fire-induced albedo change in interior Alaska","docAbstract":"

The albedo change caused by both fires and subsequent succession is spatially heterogeneous, leading to the need to assess the spatiotemporal variation of surface shortwave forcing (SSF) as a component to quantify the climate impacts of high-latitude fires. We used an image reconstruction approach to compare postfire albedo with the albedo assuming fires had not occurred. Combining the fire-caused albedo change from the 2001-2010 fires in interior Alaska and the monthly surface incoming solar radiation, we examined the spatiotemporal variation of SSF in the early successional stage of around 10 years. Our results showed that while postfire albedo generally increased in fall, winter, and spring, some burned areas could show an albedo decrease during these seasons. In summer, the albedo increased for several years and then declined again. The spring SSF distribution did not show a latitudinal decrease from south to north as previously reported. The results also indicated that although the SSF is usually largely negative in the early successional years, it may not be significant during the first postfire year. The annual 2005-2010 SSF for the 2004 fire scars was -1.30, -4.40, -3.31, -4.00, -3.42, and -2.47 Wm-2. The integrated annual SSF map showed significant spatial variation with a mean of -3.15 Wm-2 and a standard deviation of 3.26 Wm-2, 16% of burned areas having positive SSF. Our results suggest that boreal deciduous fires would be less positive for climate change than boreal evergreen fires. Future research is needed to comprehensively investigate the spatiotemporal radiative and non-radiative forcings to determine the effect of boreal fires on climate.

","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfr-2014-0309","usgsCitation":"Huang, S., Dahal, D., Liu, H., Jin, S., Young, C.J., Liu, S., and Liu, S., 2015, Spatiotemporal variation of surface shortwave forcing from fire-induced albedo change in interior Alaska: Canadian Journal of Forest Research, v. 45, no. 3, p. 276-285, https://doi.org/10.1139/cjfr-2014-0309.","productDescription":"10 p.","startPage":"276","endPage":"285","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059677","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":297371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -167.16796875,\n 71.1877539181316\n ],\n [\n -140.2734375,\n 71.13098770917023\n ],\n [\n -141.15234374999997,\n 59.62332522313024\n ],\n [\n -167.51953124999997,\n 51.944264879028765\n ],\n [\n -167.16796875,\n 71.1877539181316\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2c5ee4b08de9379b375f","contributors":{"authors":[{"text":"Huang, Shengli shuang@usgs.gov","contributorId":1926,"corporation":false,"usgs":true,"family":"Huang","given":"Shengli","email":"shuang@usgs.gov","affiliations":[],"preferred":true,"id":519448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dahal, Devendra 0000-0001-9594-1249 ddahal@usgs.gov","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":5622,"corporation":false,"usgs":true,"family":"Dahal","given":"Devendra","email":"ddahal@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":519450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Heping","contributorId":117909,"corporation":false,"usgs":true,"family":"Liu","given":"Heping","affiliations":[],"preferred":false,"id":538811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":538812,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Young, Claudia J. 0000-0002-0859-7206 cyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-0859-7206","contributorId":2770,"corporation":false,"usgs":true,"family":"Young","given":"Claudia","email":"cyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":519449,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Shuang","contributorId":138814,"corporation":false,"usgs":false,"family":"Liu","given":"Shuang","email":"","affiliations":[],"preferred":false,"id":538813,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liu, Shu-Guang sliu@usgs.gov","contributorId":984,"corporation":false,"usgs":true,"family":"Liu","given":"Shu-Guang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":519447,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70139661,"text":"70139661 - 2015 - Crustal permeability: Introduction to the special issue","interactions":[],"lastModifiedDate":"2017-04-27T14:29:17","indexId":"70139661","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1765,"text":"Geofluids","active":true,"publicationSubtype":{"id":10}},"title":"Crustal permeability: Introduction to the special issue","docAbstract":"

The topic of crustal permeability is of broad interest in light of the controlling effect of permeability on diverse geologic processes and also timely in light of the practical challenges associated with emerging technologies such as hydraulic fracturing for oil and gas production (‘fracking’), enhanced geothermal systems, and geologic carbon sequestration. This special issue of Geofluids is also motivated by the historical dichotomy between the hydrogeologic concept of permeability as a static material property that exerts control on fluid flow and the perspective of economic geologists, geophysicists, and crustal petrologists who have long recognized permeability as a dynamic parameter that changes in response to tectonism, fluid production, and geochemical reactions. Issues associated with fracking, enhanced geothermal systems, and geologic carbon sequestration have already begun to promote a constructive dialog between the static and dynamic views of permeability, and here we have made a conscious effort to include both viewpoints. This special issue also focuses on the quantification of permeability, encompassing both direct measurement of permeability in the uppermost crust and inferential permeability estimates, mainly for the deeper crust.

","language":"English","publisher":"Wiley","doi":"10.1111/gfl.12118","usgsCitation":"Ingebritsen, S.E., and Gleeson, T., 2015, Crustal permeability: Introduction to the special issue: Geofluids, v. 15, no. 1-2, p. 1-10, https://doi.org/10.1111/gfl.12118.","productDescription":"10 p.","startPage":"1","endPage":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057458","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":297635,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"1-2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-06","publicationStatus":"PW","scienceBaseUri":"54dd2b6be4b08de9379b337b","chorus":{"doi":"10.1111/gfl.12118","url":"http://dx.doi.org/10.1111/gfl.12118","publisher":"Wiley-Blackwell","authors":"Ingebritsen S. E., Gleeson T.","journalName":"Geofluids","publicationDate":"11/6/2014","auditedOn":"3/14/2016"},"contributors":{"authors":[{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":539545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gleeson, Tom","contributorId":42694,"corporation":false,"usgs":false,"family":"Gleeson","given":"Tom","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":539546,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70139357,"text":"70139357 - 2015 - Using scenario planning to evaluate the impacts of climate change on wildlife populations and communities in the Florida Everglades","interactions":[],"lastModifiedDate":"2015-04-01T09:35:08","indexId":"70139357","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Using scenario planning to evaluate the impacts of climate change on wildlife populations and communities in the Florida Everglades","docAbstract":"

It is uncertain how climate change will impact hydrologic drivers of wildlife population dynamics in freshwater wetlands of the Florida Everglades, or how to accommodate this uncertainty in restoration decisions. Using projections of climate scenarios for the year 2060, we evaluated how several possible futures could affect wildlife populations (wading birds, fish, alligators, native apple snails, amphibians, threatened and invasive species) across the Everglades landscape and inform planning already underway. We used data collected from prior research and monitoring to parameterize our wildlife population models. Hydrologic data were simulated using a spatially explicit, regional-scale model. Our scenario evaluations show that expected changes in temperature, precipitation, and sea level could significantly alter important ecological functions. All of our wildlife indicators were negatively affected by scenarios with less rainfall and more evapotranspiration. Under such scenarios, habitat suitability was substantially reduced for iconic animals such as wading birds and alligators. Conversely, the increased rainfall scenario benefited aquatic prey productivity and apex predators. Cascading impacts on non-native species is speculative, but increasing temperatures could increase the time between cold events that currently limit expansion and abundance of non-native fishes, amphibians, and reptiles with natural ranges in the tropics. This scenario planning framework underscored the benefits of proceeding with Everglades restoration plans that capture and clean more freshwater with the potential to mitigate rainfall loss and postpone impacts of sea level rise.

","language":"English","publisher":"Environmental Management","doi":"10.1007/s00267-014-0397-5","usgsCitation":"Catano, C.P., Romañach, S., Beerens, J., Pearlstine, L.G., Brandt, L., Hart, K.M., Mazzotti, F., and Trexler, J.C., 2015, Using scenario planning to evaluate the impacts of climate change on wildlife populations and communities in the Florida Everglades: Environmental Management, v. 55, no. 4, p. 807-823, https://doi.org/10.1007/s00267-014-0397-5.","productDescription":"17 p.","startPage":"807","endPage":"823","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051166","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":297570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.28759765625,\n 25.110471486223346\n ],\n [\n -82.28759765625,\n 26.868180902512403\n ],\n [\n -79.8431396484375,\n 26.868180902512403\n ],\n [\n -79.8431396484375,\n 25.110471486223346\n ],\n [\n -82.28759765625,\n 25.110471486223346\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-05","publicationStatus":"PW","scienceBaseUri":"54dd2c7ee4b08de9379b3840","contributors":{"authors":[{"text":"Catano, Christopher P.","contributorId":138935,"corporation":false,"usgs":false,"family":"Catano","given":"Christopher","email":"","middleInitial":"P.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":539334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romañach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":2331,"corporation":false,"usgs":true,"family":"Romañach","given":"Stephanie S.","email":"sromanach@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":539335,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beerens, James M. 0000-0001-8143-916X","orcid":"https://orcid.org/0000-0001-8143-916X","contributorId":25440,"corporation":false,"usgs":false,"family":"Beerens","given":"James M.","affiliations":[],"preferred":false,"id":539336,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearlstine, Leonard G.","contributorId":34751,"corporation":false,"usgs":false,"family":"Pearlstine","given":"Leonard","email":"","middleInitial":"G.","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":539337,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brandt, Laura A.","contributorId":18608,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura A.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":539338,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":539322,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mazzotti, Frank J.","contributorId":100018,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":539339,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Trexler, Joel C.","contributorId":36267,"corporation":false,"usgs":false,"family":"Trexler","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":539340,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70141030,"text":"70141030 - 2015 - Quality and age of shallow groundwater in the Bakken Formation production area, Williston Basin, Montana and North Dakota","interactions":[],"lastModifiedDate":"2015-04-17T13:02:05","indexId":"70141030","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Quality and age of shallow groundwater in the Bakken Formation production area, Williston Basin, Montana and North Dakota","docAbstract":"

The quality and age of shallow groundwater in the Bakken Formation production area were characterized using data from 30 randomly distributed domestic wells screened in the upper Fort Union Formation. Comparison of inorganic and organic chemical concentrations to health based drinking-water standards, correlation analysis of concentrations with oil and gas well locations, and isotopic data give no indication that energy-development activities affected groundwater quality. It is important, however, to consider these results in the context of groundwater age. Most samples were recharged before the early 1950s and had 14C ages ranging from 30,000 years. Thus, domestic wells may not be as well suited for detecting contamination associated with recent surface spills as shallower wells screened near the water table. Old groundwater could be contaminated directly by recent subsurface leaks from imperfectly cemented oil and gas wells, but horizontal groundwater velocities calculated from 14C ages imply that the contaminants would still be less than 0.5 km from their source. For the wells sampled in this study, the median distance to the nearest oil and gas well was 4.6 km. Because of the slow velocities, a long-term commitment to groundwater monitoring in the upper Fort Union Formation is needed to assess the effects of energy development on groundwater quality. In conjunction with that effort, monitoring could be done closer to energy-development activities to increase the likelihood of early detection of groundwater contamination if it did occur.

","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.12296","usgsCitation":"McMahon, P.B., Caldwell, R.R., Galloway, J.M., Valder, J., and Hunt, A.G., 2015, Quality and age of shallow groundwater in the Bakken Formation production area, Williston Basin, Montana and North Dakota: Groundwater, v. 53, no. S1, p. 81-94, https://doi.org/10.1111/gwat.12296.","productDescription":"14 p.","startPage":"81","endPage":"94","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059302","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":297944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","otherGeospatial":"Bakken Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.9501953125,\n 46.76996843356982\n ],\n [\n -113.9501953125,\n 49.009050809382046\n ],\n [\n -99.7119140625,\n 49.009050809382046\n ],\n [\n -99.7119140625,\n 46.76996843356982\n ],\n [\n -113.9501953125,\n 46.76996843356982\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"53","issue":"S1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-13","publicationStatus":"PW","scienceBaseUri":"54dd2c2fe4b08de9379b369a","chorus":{"doi":"10.1111/gwat.12296","url":"http://dx.doi.org/10.1111/gwat.12296","publisher":"Wiley-Blackwell","authors":"McMahon P.B., Caldwell R.R., Galloway J.M., Valder J.F., Hunt A.G.","journalName":"Groundwater","publicationDate":"11/13/2014","auditedOn":"12/15/2014"},"contributors":{"authors":[{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540530,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Rodney R. 0000-0002-2588-715X caldwell@usgs.gov","orcid":"https://orcid.org/0000-0002-2588-715X","contributorId":2577,"corporation":false,"usgs":true,"family":"Caldwell","given":"Rodney","email":"caldwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":540531,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galloway, Joel M. 0000-0002-9836-9724 jgallowa@usgs.gov","orcid":"https://orcid.org/0000-0002-9836-9724","contributorId":1562,"corporation":false,"usgs":true,"family":"Galloway","given":"Joel","email":"jgallowa@usgs.gov","middleInitial":"M.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540532,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valder, Joshua F. 0000-0003-3733-8868 jvalder@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-8868","contributorId":1431,"corporation":false,"usgs":true,"family":"Valder","given":"Joshua F.","email":"jvalder@usgs.gov","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":540533,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":540534,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70160447,"text":"70160447 - 2015 - Late Holocene sea- and land-level change on the U.S. southeastern Atlantic Coast","interactions":[],"lastModifiedDate":"2015-12-18T15:39:40","indexId":"70160447","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Late Holocene sea- and land-level change on the U.S. southeastern Atlantic Coast","docAbstract":"

Late Holocene relative sea-level (RSL) reconstructions can be used to estimate rates of land-level (subsidence or uplift) change and therefore to modify global sea-level projections for regional conditions. These reconstructions also provide the long-term benchmark against which modern trends are compared and an opportunity to understand the response of sea level to past climate variability. To address a spatial absence of late Holocene data in Florida and Georgia, we reconstructed ~ 1.3 m of RSL rise in northeastern Florida (USA) during the past ~ 2600 years using plant remains and foraminifera in a dated core of high salt-marsh sediment. The reconstruction was fused with tide-gauge data from nearby Fernandina Beach, which measured 1.91 ± 0.26 mm/year of RSL rise since 1900 CE. The average rate of RSL rise prior to 1800 CE was 0.41 ± 0.08 mm/year. Assuming negligible change in global mean sea level from meltwater input/removal and thermal expansion/contraction, this sea-level history approximates net land-level (subsidence and geoid) change, principally from glacio-isostatic adjustment. Historic rates of rise commenced at 1850–1890 CE and it is virtually certain (P = 0.99) that the average rate of 20th century RSL rise in northeastern Florida was faster than during any of the preceding 26 centuries. The linearity of RSL rise in Florida is in contrast to the variability reconstructed at sites further north on the U.S. Atlantic coast and may suggest a role for ocean dynamic effects in explaining these more variable RSL reconstructions. Comparison of the difference between reconstructed rates of late Holocene RSL rise and historic trends measured by tide gauges indicates that 20th century sea-level trends along the U.S. Atlantic coast were not dominated by the characteristic spatial fingerprint of melting of the Greenland Ice Sheet.

","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.margeo.2014.07.010","usgsCitation":"Kemp, A., Bernhardt, C.E., Horton, B.P., Kopp, R., Vane, C.H., Peltier, W.R., Hawkes, A., Donnelly, J., Parnell, A.C., and Cahill, N., 2015, Late Holocene sea- and land-level change on the U.S. southeastern Atlantic Coast: Marine Geology, v. 357, p. 90-100, https://doi.org/10.1016/j.margeo.2014.07.010.","productDescription":"11 p.","startPage":"90","endPage":"100","numberOfPages":"11","ipdsId":"IP-058206","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":472462,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://mural.maynoothuniversity.ie/14567/1/NC_late%20holocene.pdf","text":"External Repository"},{"id":312547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.68322086334229,\n 30.572090062678555\n ],\n [\n -81.68322086334229,\n 30.597434228713674\n ],\n [\n -81.64442539215088,\n 30.597434228713674\n ],\n [\n -81.64442539215088,\n 30.572090062678555\n ],\n [\n -81.68322086334229,\n 30.572090062678555\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"357","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56753c3ee4b0da412f4f8bf1","contributors":{"authors":[{"text":"Kemp, Andrew C.","contributorId":39674,"corporation":false,"usgs":true,"family":"Kemp","given":"Andrew C.","affiliations":[],"preferred":false,"id":582928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":582927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horton, Benjamin P.","contributorId":63641,"corporation":false,"usgs":true,"family":"Horton","given":"Benjamin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":582929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kopp, Robert E.","contributorId":64570,"corporation":false,"usgs":true,"family":"Kopp","given":"Robert E.","affiliations":[],"preferred":false,"id":582930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vane, Christopher H.","contributorId":88255,"corporation":false,"usgs":true,"family":"Vane","given":"Christopher","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":582931,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peltier, W. Richard","contributorId":150752,"corporation":false,"usgs":false,"family":"Peltier","given":"W.","email":"","middleInitial":"Richard","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":582932,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hawkes, Andrea D.","contributorId":20240,"corporation":false,"usgs":true,"family":"Hawkes","given":"Andrea D.","affiliations":[],"preferred":false,"id":582933,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Donnelly, Jeffrey P.","contributorId":91613,"corporation":false,"usgs":true,"family":"Donnelly","given":"Jeffrey P.","affiliations":[],"preferred":false,"id":582934,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Parnell, Andrew C.","contributorId":150753,"corporation":false,"usgs":false,"family":"Parnell","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":18091,"text":"University College Dublin","active":true,"usgs":false}],"preferred":false,"id":582935,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cahill, Niamh","contributorId":150754,"corporation":false,"usgs":false,"family":"Cahill","given":"Niamh","email":"","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false},{"id":18091,"text":"University College Dublin","active":true,"usgs":false}],"preferred":false,"id":582936,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70128671,"text":"70128671 - 2015 - Testing the use of bulk organic δ13C, δ15N, and Corg:Ntot ratios to estimate subsidence during the 1964 great Alaska earthquake","interactions":[],"lastModifiedDate":"2018-04-04T16:09:39","indexId":"70128671","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Testing the use of bulk organic δ13C, δ15N, and Corg:Ntot ratios to estimate subsidence during the 1964 great Alaska earthquake","docAbstract":"

During the Mw 9.2 1964 great Alaska earthquake, Turnagain Arm near Girdwood, Alaska subsided 1.7 ± 0.1 m based on pre- and postearthquake leveling. The coseismic subsidence in 1964 caused equivalent sudden relative sea-level (RSL) rise that is stratigraphically preserved as mud-over-peat contacts where intertidal silt buried peaty marsh surfaces. Changes in intertidal microfossil assemblages across these contacts have been used to estimate subsidence in 1964 by applying quantitative microfossil transfer functions to reconstruct corresponding RSL rise. Here, we review the use of organic stable C and N isotope values and Corg:Ntot ratios as alternative proxies for reconstructing coseismic RSL changes, and report independent estimates of subsidence in 1964 by using δ13C values from intertidal sediment to assess RSL change caused by the earthquake. We observe that surface sediment δ13C values systematically decrease by ∼4‰ over the ∼2.5 m increase in elevation along three 60- to 100-m-long transects extending from intertidal mud flat to upland environments. We use a straightforward linear regression to quantify the relationship between modern sediment δ13C values and elevation (n = 84, R2 = 0.56). The linear regression provides a slope–intercept equation used to reconstruct the paleoelevation of the site before and after the earthquake based on δ13C values in sandy silt above and herbaceous peat below the 1964 contact. The regression standard error (average = ±0.59‰) reflects the modern isotopic variability at sites of similar surface elevation, and is equivalent to an uncertainty of ±0.4 m elevation with respect to Mean Higher High Water. To reduce potential errors in paleoelevation and subsidence estimates, we analyzed multiple sediment δ13C values in nine cores on a shore-perpendicular transect at Bird Point. Our method estimates 1.3 ± 0.4 m of coseismic RSL rise across the 1964 contact by taking the arithmetic mean of the differences (n = 9) between reconstructed elevations for sediment above and below the 1964 earthquake subsidence contact. This estimate compares well with independent subsidence estimates derived from post-earthquake leveling in Turnagain Arm, and from microfossil transfer functions at Girdwood (1.50 ± 0.32 m). While our results support the use of bulk organic δ13C for reconstructing RSL change in southern Alaska, the variability of stable isotope values in modern and buried intertidal sediment required the analysis of multiple samples to reduce error.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2014.09.031","usgsCitation":"Bender, A.M., Witter, R., and Rogers, M., 2015, Testing the use of bulk organic δ13C, δ15N, and Corg:Ntot ratios to estimate subsidence during the 1964 great Alaska earthquake: Quaternary Science Reviews, v. 113, p. 134-146, https://doi.org/10.1016/j.quascirev.2014.09.031.","productDescription":"13 p.","startPage":"134","endPage":"146","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060286","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":297372,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -167.16796875,\n 71.1877539181316\n ],\n [\n -140.2734375,\n 71.13098770917023\n ],\n [\n -141.15234374999997,\n 59.62332522313024\n ],\n [\n -167.51953124999997,\n 51.944264879028765\n ],\n [\n -167.16796875,\n 71.1877539181316\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"113","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2c68e4b08de9379b37aa","contributors":{"authors":[{"text":"Bender, Adrian M. 0000-0001-7469-1957 abender@usgs.gov","orcid":"https://orcid.org/0000-0001-7469-1957","contributorId":4963,"corporation":false,"usgs":true,"family":"Bender","given":"Adrian","email":"abender@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":519748,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":519747,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rogers, Matthew","contributorId":120088,"corporation":false,"usgs":false,"family":"Rogers","given":"Matthew","affiliations":[],"preferred":false,"id":519749,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70132472,"text":"70132472 - 2015 - Uncertainty estimates in broadband seismometer sensitivities using microseisms","interactions":[],"lastModifiedDate":"2015-03-19T15:49:02","indexId":"70132472","displayToPublicDate":"2014-10-30T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2453,"text":"Journal of Seismology","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty estimates in broadband seismometer sensitivities using microseisms","docAbstract":"

The midband sensitivity of a seismic instrument is one of the fundamental parameters used in published station metadata. Any errors in this value can compromise amplitude estimates in otherwise high-quality data. To estimate an upper bound in the uncertainty of the midband sensitivity for modern broadband instruments, we compare daily microseism (4- to 8-s period) amplitude ratios between the vertical components of colocated broadband sensors across the IRIS/USGS (network code IU) seismic network. We find that the mean of the 145,972 daily ratios used between 2002 and 2013 is 0.9895 with a standard deviation of 0.0231. This suggests that the ratio between instruments shows a small bias and considerable scatter. We also find that these ratios follow a standard normal distribution (R 2 = 0.95442), which suggests that the midband sensitivity of an instrument has an error of no greater than ±6 % with a 99 % confidence interval. This gives an upper bound on the precision to which we know the sensitivity of a fielded instrument.

","language":"English","publisher":"Springer","doi":"10.1007/s10950-014-9467-7","usgsCitation":"Ringler, A.T., Storm, T., Gee, L., Hutt, C.R., and Wilson, D., 2015, Uncertainty estimates in broadband seismometer sensitivities using microseisms: Journal of Seismology, v. 19, no. 2, p. 317-327, https://doi.org/10.1007/s10950-014-9467-7.","productDescription":"11 p.","startPage":"317","endPage":"327","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059886","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":296151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-10-30","publicationStatus":"PW","scienceBaseUri":"546c763de4b0f4a3478a61d7","contributors":{"authors":[{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":3946,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":523246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storm, Tyler L. tstorm@usgs.gov","contributorId":4073,"corporation":false,"usgs":true,"family":"Storm","given":"Tyler L.","email":"tstorm@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":523247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gee, Lind S. lgee@usgs.gov","contributorId":2247,"corporation":false,"usgs":true,"family":"Gee","given":"Lind S.","email":"lgee@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":523248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hutt, Charles R. 0000-0001-9033-9195 bhutt@usgs.gov","orcid":"https://orcid.org/0000-0001-9033-9195","contributorId":1622,"corporation":false,"usgs":true,"family":"Hutt","given":"Charles","email":"bhutt@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":523249,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, David C. dwilson@usgs.gov","contributorId":4588,"corporation":false,"usgs":true,"family":"Wilson","given":"David C.","email":"dwilson@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":523250,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70145721,"text":"70145721 - 2015 - Palila Restoration Research, 1996−2012. Summary and management implications","interactions":[],"lastModifiedDate":"2018-01-04T12:45:04","indexId":"70145721","displayToPublicDate":"2014-10-29T18:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":414,"text":"Technical Report","active":false,"publicationSubtype":{"id":9}},"seriesNumber":"HCSU-046A","title":"Palila Restoration Research, 1996−2012. Summary and management implications","docAbstract":"

The Palila Restoration Project was initiated in 1996 by the U.S. Geological Survey to assist government agencies mitigate the effects of realigning Saddle Road (Highway 200) through Palila Critical Habitat (U.S. Fish and Wildlife Service 1998, Federal Highway Administration 1999). Ecological research on the palila (Loxioides bailleui), an endangered Hawaiian forest bird, carried out by the U.S. Geological Survey (formerly organized as the Research Division of U.S. Fish and Wildlife Service) since 1987 and research conducted by the Palila Restoration Project provided the scientific bases for developing a recovery strategy (U.S. Fish and Wildlife Service 2006) and its adaptive implementation. The main objectives of the Palila Restoration Project were to develop techniques for reintroducing the palila to a portion of its former range, investigate the biological threats to the palila and its habitat, and synthesize the existing body of ecological knowledge concerning the palila. Five broad study themes formed the research framework: 1. Population reintroduction and restoration 2. Demography and breeding ecology 3. Habitat use and food ecology 4. Vegetation ecology 5. Predator ecology and management An element that was not included in the research program of the project was the ecology and management of introduced ungulates, which has historically constituted the single greatest threat to Palila Critical Habitat (Banko et al. 2009). The absence of ungulate studies should not be interpreted to mean that we believe ungulates no longer damage palila habitat. Other research has already established that removing alien browsers and grazers from Mauna Kea is essential for the recovery of the subalpine forest on which palila now depend (Scowcroft and Giffin 1983; Scowcroft and Sakai 1983; Scowcroft and Conrad 1988, 1992; Hess et al. 1999). Moreover, the Federal District Court of Hawai‘i has ordered the State of Hawai‘i to remove browsing ungulates from Palila Critical Habitat (Banko et al. 2009, Hess and Banko 2011). This final report summarizes results of Palila Restoration Project research from December 1996 to December 2012. Even though some results contained in this report have been published in scientific journals and other technical reports (Appendix I), they are included here to provide a comprehensive chronicle of all project activities.

","language":"English","publisher":"University of Hawaii at Hilo","publisherLocation":"Hilo, HI","usgsCitation":"Banko, P.C., Farmer, C., Dougill, S., and Johnson, L., 2015, Palila Restoration Research, 1996−2012. Summary and management implications: Technical Report HCSU-046A, Report: ii, 70 p.","productDescription":"Report: ii, 70 p.","startPage":"1","endPage":"70","numberOfPages":"74","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060592","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a9ad6be4b05e859bdfba8c","contributors":{"authors":[{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":544312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farmer, Chris cfarmer@usgs.gov","contributorId":3681,"corporation":false,"usgs":true,"family":"Farmer","given":"Chris","email":"cfarmer@usgs.gov","affiliations":[],"preferred":true,"id":544313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dougill, Steve","contributorId":140104,"corporation":false,"usgs":false,"family":"Dougill","given":"Steve","affiliations":[{"id":13385,"text":"University of Hawaii at Hilo Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":544314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Luanne","contributorId":140108,"corporation":false,"usgs":false,"family":"Johnson","given":"Luanne","email":"","affiliations":[{"id":13385,"text":"University of Hawaii at Hilo Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":544315,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70131478,"text":"70131478 - 2015 - Permafrost-associated gas hydrate: is it really approximately 1% of the global system?","interactions":[],"lastModifiedDate":"2015-02-23T16:20:09","indexId":"70131478","displayToPublicDate":"2014-10-29T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3821,"text":"Journal of Chemical & Engineering Data","active":true,"publicationSubtype":{"id":10}},"title":"Permafrost-associated gas hydrate: is it really approximately 1% of the global system?","docAbstract":"

Permafrost-associated gas hydrates are often assumed to contain ∼1 % of the global gas-in-place in gas hydrates based on a study26 published over three decades ago. As knowledge of permafrost-associated gas hydrates has grown, it has become clear that many permafrost-associated gas hydrates are inextricably linked to an associated conventional petroleum system, and that their formation history (trapping of migrated gas in situ during Pleistocene cooling) is consistent with having been sourced at least partially in nearby thermogenic gas deposits. Using modern data sets that constrain the distribution of continuous permafrost onshore5 and subsea permafrost on circum-Arctic Ocean continental shelves offshore and that estimate undiscovered conventional gas within arctic assessment units,16 the done here reveals where permafrost-associated gas hydrates are most likely to occur, concluding that Arctic Alaska and the West Siberian Basin are the best prospects. A conservative estimate is that 20 Gt C (2.7·1013 kg CH4) may be sequestered in permafrost-associated gas hydrates if methane were the only hydrate-former. This value is slightly more than 1 % of modern estimates (corresponding to 1600 Gt C to 1800 Gt C2,22) for global gas-in-place in methane hydrates and about double the absolute estimate (11.2 Gt C) made in 1981.26

","language":"English","publisher":"American Chemical Society","doi":"10.1021/je500770m","usgsCitation":"Ruppel, C., 2015, Permafrost-associated gas hydrate: is it really approximately 1% of the global system?: Journal of Chemical & Engineering Data, v. 60, no. 2, p. 429-436, https://doi.org/10.1021/je500770m.","productDescription":"8 p.","startPage":"429","endPage":"436","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060410","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":296452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-10-29","publicationStatus":"PW","scienceBaseUri":"548193bee4b0aa6d778520f0","chorus":{"doi":"10.1021/je500770m","url":"http://dx.doi.org/10.1021/je500770m","publisher":"American Chemical Society (ACS)","authors":"Ruppel C.","journalName":"Journal of Chemical & Engineering Data","publicationDate":"2/12/2015","auditedOn":"12/1/2014"},"contributors":{"authors":[{"text":"Ruppel, Carolyn cruppel@usgs.gov","contributorId":2015,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn","email":"cruppel@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":521234,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70158599,"text":"70158599 - 2015 - Seasonal dynamics of zooplankton in Columbia–Snake River reservoirs,with special emphasis on the invasive copepod Pseudodiaptomus forbesi","interactions":[],"lastModifiedDate":"2016-12-19T11:55:05","indexId":"70158599","displayToPublicDate":"2014-10-15T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal dynamics of zooplankton in Columbia–Snake River reservoirs,with special emphasis on the invasive copepod Pseudodiaptomus forbesi","docAbstract":"
The Asian copepod Pseudodiaptomus forbesi has recently become established in the Columbia River. However, little is known about its ecology and effects on invaded ecosystems. We undertook a 2-year (July 2009 to June 2011) field study of the mesozooplankton in four reservoirs in the Columbia and Snake Rivers, with emphasis on the relation of the seasonal variation in distribution and abundance of P. forbesi to environmental variables. Pseudodiaptomus forbesi was abundant in three reservoirs; the zooplankton community of the fourth reservoir contained no known non-indigenous taxa. The composition and seasonal succession of zooplankton were similar in the three invaded reservoirs: a bloom of rotifers occurred in spring, native cyclopoid and cladoceran species peaked in abundance in summer, and P. forbesi was most abundant in late summer and autumn. In the uninvaded reservoir, total zooplankton abundance was very low year-round. Multivariate ordination indicated that temperature and dissolved oxygen were strongly associated with zooplankton community structure, with P. forbesi appearing to exhibit a single generation per year . The broad distribution and high abundance of P. forbesi in the Columbia–Snake River System could result in ecosystem level effects in areas intensively managed to improve conditions for salmon and other commercially and culturally important fish species. 
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/ai.2015.10.1.03","usgsCitation":"Emerson, J.E., Bollens, S.M., and Counihan, T.D., 2015, Seasonal dynamics of zooplankton in Columbia–Snake River reservoirs,with special emphasis on the invasive copepod Pseudodiaptomus forbesi: Aquatic Invasions, v. 10, no. 1, p. 25-40, https://doi.org/10.3391/ai.2015.10.1.03.","productDescription":"16 p.","startPage":"25","endPage":"40","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063638","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":472463,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2015.10.1.03","text":"Publisher Index Page"},{"id":309572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Columbia River, Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.981689453125,\n 46.79253827035982\n ],\n [\n -120.003662109375,\n 46.68713141244413\n ],\n [\n -119.8773193359375,\n 46.581518465658014\n ],\n [\n -119.498291015625,\n 46.66451741754235\n ],\n [\n -119.33349609375,\n 46.51351558059737\n ],\n [\n -119.3115234375,\n 46.32417161725691\n ],\n [\n -119.2071533203125,\n 46.13417004624326\n ],\n [\n -119.22912597656249,\n 45.99314540468519\n ],\n [\n -119.6575927734375,\n 45.96260622242165\n ],\n [\n -120.157470703125,\n 45.874712248904764\n ],\n [\n -120.7012939453125,\n 45.78284835197676\n ],\n [\n -121.03912353515626,\n 45.69275137290873\n ],\n [\n -121.36322021484374,\n 45.733025435949735\n ],\n [\n -121.61590576171876,\n 45.74644367422241\n ],\n [\n -121.61865234375,\n 45.663966415824056\n ],\n [\n -121.2945556640625,\n 45.65628792636447\n ],\n [\n -121.14624023437499,\n 45.583289756006316\n ],\n [\n -120.89904785156251,\n 45.60250901510299\n ],\n [\n -120.5804443359375,\n 45.694669843547246\n ],\n [\n -120.157470703125,\n 45.66780526567164\n ],\n [\n -119.94873046875,\n 45.763690956618674\n ],\n [\n -119.46533203125,\n 45.867062714815475\n ],\n [\n -119.0972900390625,\n 45.89000815866184\n ],\n [\n -118.86657714843749,\n 46.00840867976967\n ],\n [\n -118.83911132812499,\n 46.20264638061019\n ],\n [\n -118.61938476562499,\n 46.37346430137335\n ],\n [\n -118.5150146484375,\n 46.479482189368646\n ],\n [\n -118.6138916015625,\n 46.53619267489863\n ],\n [\n -118.7017822265625,\n 46.449212403852584\n ],\n [\n -118.88305664062499,\n 46.31658418182218\n ],\n [\n -119.06982421874999,\n 46.27483447871404\n ],\n [\n -119.2071533203125,\n 46.45299704748289\n ],\n [\n -119.27307128906249,\n 46.60039303734547\n ],\n [\n -119.39941406249999,\n 46.71350244599995\n ],\n [\n -119.564208984375,\n 46.751153008636884\n ],\n [\n -119.7509765625,\n 46.68713141244413\n ],\n [\n -119.871826171875,\n 46.758679967095574\n ],\n [\n -119.88281249999999,\n 46.79253827035982\n ],\n [\n -119.981689453125,\n 46.79253827035982\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56139f4fe4b0ba4884c60fbd","contributors":{"authors":[{"text":"Emerson, Joshua E.","contributorId":148957,"corporation":false,"usgs":false,"family":"Emerson","given":"Joshua","email":"","middleInitial":"E.","affiliations":[{"id":17602,"text":"School of the Environment, Washington State University, Vancouver, WA 98686","active":true,"usgs":false}],"preferred":false,"id":576261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bollens, Stephen M. 0000-0001-9214-9037","orcid":"https://orcid.org/0000-0001-9214-9037","contributorId":148958,"corporation":false,"usgs":false,"family":"Bollens","given":"Stephen","email":"","middleInitial":"M.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":576262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Counihan, Timothy D. 0000-0003-4967-6514 tcounihan@usgs.gov","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":4211,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy","email":"tcounihan@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":576260,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70128794,"text":"70128794 - 2015 - Machine learning for predicting soil classes in three semi-arid landscapes","interactions":[],"lastModifiedDate":"2014-10-14T15:20:17","indexId":"70128794","displayToPublicDate":"2014-10-14T15:14:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"Machine learning for predicting soil classes in three semi-arid landscapes","docAbstract":"

Mapping the spatial distribution of soil taxonomic classes is important for informing soil use and management decisions. Digital soil mapping (DSM) can quantitatively predict the spatial distribution of soil taxonomic classes. Key components of DSM are the method and the set of environmental covariates used to predict soil classes. Machine learning is a general term for a broad set of statistical modeling techniques. Many different machine learning models have been applied in the literature and there are different approaches for selecting covariates for DSM. However, there is little guidance as to which, if any, machine learning model and covariate set might be optimal for predicting soil classes across different landscapes.

\n
\n

Our objective was to compare multiple machine learning models and covariate sets for predicting soil taxonomic classes at three geographically distinct areas in the semi-arid western United States of America (southern New Mexico, southwestern Utah, and northeastern Wyoming). All three areas were the focus of digital soil mapping studies. Sampling sites at each study area were selected using conditioned Latin hypercube sampling (cLHS). We compared models that had been used in other DSM studies, including clustering algorithms, discriminant analysis, multinomial logistic regression, neural networks, tree based methods, and support vector machine classifiers. Tested machine learning models were divided into three groups based on model complexity: simple, moderate, and complex. We also compared environmental covariates derived from digital elevation models and Landsat imagery that were divided into three different sets: 1) covariates selected a priori by soil scientists familiar with each area and used as input into cLHS, 2) the covariates in set 1 plus 113 additional covariates, and 3) covariates selected using recursive feature elimination.

\n
\n

Overall, complex models were consistently more accurate than simple or moderately complex models. Random forests (RF) using covariates selected via recursive feature elimination was consistently the most accurate, or was among the most accurate, classifiers between study areas and between covariate sets within each study area. We recommend that for soil taxonomic class prediction, complex models and covariates selected by recursive feature elimination be used.

\n
\n

Overall classification accuracy in each study area was largely dependent upon the number of soil taxonomic classes and the frequency distribution of pedon observations between taxonomic classes. Individual subgroup class accuracy was generally dependent upon the number of soil pedon observations in each taxonomic class. The number of soil classes is related to the inherent variability of a given area. The imbalance of soil pedon observations between classes is likely related to cLHS. Imbalanced frequency distributions of soil pedon observations between classes must be addressed to improve model accuracy. Solutions include increasing the number of soil pedon observations in classes with few observations or decreasing the number of classes. Spatial predictions using the most accurate models generally agree with expected soil–landscape relationships. Spatial prediction uncertainty was lowest in areas of relatively low relief for each study area.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geoderma","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.geoderma.2014.09.019","usgsCitation":"Brungard, C.W., Boettinger, J.L., Duniway, M.C., Wills, S., and Edwards, T.C., 2015, Machine learning for predicting soil classes in three semi-arid landscapes: Geoderma, v. 239-240, p. 68-83, https://doi.org/10.1016/j.geoderma.2014.09.019.","productDescription":"16 p.","startPage":"68","endPage":"83","ipdsId":"IP-055747","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":295328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295318,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.geoderma.2014.09.019"}],"country":"United States","state":"New Mexico, Utah, Wyoming","volume":"239-240","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"543e2d06e4b0fd76af69cedc","contributors":{"authors":[{"text":"Brungard, Colby W.","contributorId":99488,"corporation":false,"usgs":true,"family":"Brungard","given":"Colby","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":503225,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boettinger, Janis L.","contributorId":82239,"corporation":false,"usgs":true,"family":"Boettinger","given":"Janis","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":503223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":503222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wills, Skye A.","contributorId":92600,"corporation":false,"usgs":true,"family":"Wills","given":"Skye A.","affiliations":[],"preferred":false,"id":503224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edwards, Thomas C. Jr. 0000-0002-0773-0909 tce@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-0909","contributorId":2061,"corporation":false,"usgs":true,"family":"Edwards","given":"Thomas","suffix":"Jr.","email":"tce@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":false,"id":503221,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70128483,"text":"tm4A10 - 2015 - User guide to Exploration and Graphics for RivEr Trends (EGRET) and dataRetrieval: R packages for hydrologic data","interactions":[],"lastModifiedDate":"2021-03-25T14:13:34.167466","indexId":"tm4A10","displayToPublicDate":"2014-10-09T09:41:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-A10","title":"User guide to Exploration and Graphics for RivEr Trends (EGRET) and dataRetrieval: R packages for hydrologic data","docAbstract":"

Evaluating long-term changes in river conditions (water quality and discharge) is an important use of hydrologic data. To carry out such evaluations, the hydrologist needs tools to facilitate several key steps in the process: acquiring the data records from a variety of sources, structuring it in ways that facilitate the analysis, processing the data with routines that extract information about changes that may be happening, and displaying findings with graphical techniques. A pair of tightly linked R packages, called dataRetrieval and EGRET (Exploration and Graphics for RivEr Trends), have been developed for carrying out each of these steps in an integrated manner. They are designed to easily accept data from three sources: U.S. Geological Survey hydrologic data, U.S. Environmental Protection Agency (EPA) STORET data, and user-supplied flat files. The dataRetrieval package not only serves as a “front end” to the EGRET package, it can also be used to easily download many types of hydrologic data and organize it in ways that facilitate many other hydrologic applications. The EGRET package has components oriented towards the description of long-term changes in streamflow statistics (high flow, average flow, and low flow) as well as changes in water quality. For the water-quality analysis, it uses Weighted Regressions on Time, Discharge and Season (WRTDS) to describe long-term trends in both concentration and flux. EGRET also creates a wide range of graphical presentations of the water-quality data and of the WRTDS results. This report serves as a user guide to these two R packages, providing detailed guidance on installation and use of the software, documentation of the analysis methods used, as well as guidance on some of the kinds of questions and approaches that the software can facilitate.

","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Statistical analysis in Book 4 Hydrologic Analysis and Interpretation","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4A10","usgsCitation":"Hirsch, R.M., and De Cicco, L., 2015, User guide to Exploration and Graphics for RivEr Trends (EGRET) and dataRetrieval: R packages for hydrologic data (Version 1.0: Originally posted October 8, 2014; Version 2.0: February 5, 2015): U.S. Geological Survey Techniques and Methods 4-A10, Report: vii, 93 p.; 2 Appendixes, https://doi.org/10.3133/tm4A10.","productDescription":"Report: vii, 93 p.; 2 Appendixes","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056100","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":438730,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X4L3GE","text":"USGS data release","linkHelpText":"dataRetrieval"},{"id":297766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/04/a10/images/coverthb.jpg"},{"id":295115,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/04/a10/pdf/tm4A10_appendix_1.pdf","text":"Appendix 1: data retrieval vignette","size":"472 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 1: data retrieval vignette"},{"id":295086,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/04/a10/"},{"id":295114,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/a10/pdf/tm4A10.pdf","text":"Report","size":"6.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":295116,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/04/a10/pdf/tm4A10_appendix_2.pdf","text":"Appendix 2: EGRET vignette","size":"1.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 2: EGRET vignette"}],"edition":"Version 1.0: Originally posted October 8, 2014; Version 2.0: February 5, 2015","publicComments":"This report is Chapter 10 of Section A: Statistical analysis in Book 4 Hydrologic Analysis and Interpretation.","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54379589e4b08a816ca63613","contributors":{"authors":[{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":502921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Cicco, Laura A. 0000-0002-3915-9487","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":35255,"corporation":false,"usgs":true,"family":"De Cicco","given":"Laura A.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":false,"id":502922,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70048648,"text":"70048648 - 2015 - Ungulate exclusion, conifer thinning and mule deer forage in northeastern New Mexico","interactions":[],"lastModifiedDate":"2014-10-16T08:38:28","indexId":"70048648","displayToPublicDate":"2014-10-08T12:55:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Ungulate exclusion, conifer thinning and mule deer forage in northeastern New Mexico","docAbstract":"The southwestern United States has experienced expansion of conifer species (Juniperus spp. and Pinus ponderosa) into areas of semi-arid grassland over the past century. The expansion of conifers can limit palatable forage and reduce grass and forb communities. Conifer species are sometimes thinned through hydraulic mulching or selective cutting. We assessed the effects of these treatments on mule deer (Odocoileus hemionus) habitat in northeastern New Mexico to determine if conifer thinning improved cover of preferred forage species for mule deer in areas with and without ungulates. We measured plant cover and occurrence of preferred forage species in the summers of 2011 and 2012. An ongoing regional drought probably reduced vegetation response, with preferred forage species and herbaceous cover responding to conifer thinning or ungulate exclusion immediately following treatment, but not the following year. In 2011, areas that received thinning treatments had a higher abundance of preferred forage when compared to sites with no treatment. Grass coverage exhibited an immediate response in 2011, with ungulate exclosures containing 8% more coverage than areas without exclosures. The results suggest that conifer thinning and ungulate exclusion may elicit a positive response, however in the presence of drought; the positive effects are only short-term.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Arid Environments","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2014.09.008","usgsCitation":"Kramer, D.W., Sorensen, G.E., Taylor, C.A., Cox, R.D., Gipson, P.S., and Cain, J.W., 2015, Ungulate exclusion, conifer thinning and mule deer forage in northeastern New Mexico: Journal of Arid Environments, v. 113, p. 29-34, https://doi.org/10.1016/j.jaridenv.2014.09.008.","productDescription":"6 p.","startPage":"29","endPage":"34","numberOfPages":"6","ipdsId":"IP-043710","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":295095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295094,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jaridenv.2014.09.008"}],"country":"United States","state":"New Mexico","volume":"113","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54364405e4b0a4f4b46a31cd","contributors":{"authors":[{"text":"Kramer, David W.","contributorId":15128,"corporation":false,"usgs":true,"family":"Kramer","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":485281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sorensen, Grant E.","contributorId":41762,"corporation":false,"usgs":true,"family":"Sorensen","given":"Grant","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":485283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Chase A.","contributorId":107215,"corporation":false,"usgs":true,"family":"Taylor","given":"Chase","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":485285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cox, Robert D.","contributorId":26240,"corporation":false,"usgs":true,"family":"Cox","given":"Robert","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":485282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gipson, Philip S.","contributorId":71495,"corporation":false,"usgs":true,"family":"Gipson","given":"Philip","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":485284,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":485280,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70120425,"text":"70120425 - 2015 - Development of a spatially universal framework for classifying stream assemblages with application to conservation planning for Great Lakes lotic fish communities","interactions":[],"lastModifiedDate":"2015-03-09T10:23:05","indexId":"70120425","displayToPublicDate":"2014-10-01T14:27:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Development of a spatially universal framework for classifying stream assemblages with application to conservation planning for Great Lakes lotic fish communities","docAbstract":"

Classifications are typically specific to particular issues or areas, leading to patchworks of subjectively defined spatial units. Stream conservation is hindered by the lack of a universal habitat classification system and would benefit from an independent hydrology-guided spatial framework of units encompassing all aquatic habitats at multiple spatial scales within large regions. We present a system that explicitly separates the spatial framework from any particular classification developed from the framework. The framework was constructed from landscape variables that are hydrologically and biologically relevant, covered all space within the study area, and was nested hierarchically and spatially related at scales ranging from the stream reach to the entire region; classifications may be developed from any subset of the 9 basins, 107 watersheds, 459 subwatersheds, or 10,000s of valley segments or stream reaches. To illustrate the advantages of this approach, we developed a fish-guided classification generated from a framework for the Great Lakes region that produced a mosaic of habitat units which, when aggregated, formed larger patches of more general conditions at progressively broader spatial scales. We identified greater than 1,200 distinct fish habitat types at the valley segment scale, most of which were rare. Comparisons of biodiversity and species assemblages are easily examined at any scale. This system can identify and quantify habitat types, evaluate habitat quality for conservation and/or restoration, and assist managers and policymakers with prioritization of protection and restoration efforts. Similar spatial frameworks and habitat classifications can be developed for any organism in any riverine ecosystem.

","language":"English","publisher":"Society for Ecological Restoration","doi":"10.1111/rec.12146","usgsCitation":"McKenna, J., Schaeffer, J., Stewart, J.S., and Slattery, M.T., 2015, Development of a spatially universal framework for classifying stream assemblages with application to conservation planning for Great Lakes lotic fish communities: Restoration Ecology, v. 23, no. 2, p. 167-178, https://doi.org/10.1111/rec.12146.","productDescription":"12 p.","startPage":"167","endPage":"178","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051855","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":294729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294728,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/rec.12146"}],"country":"United States","state":"Michigan, Minnesota, New York, Ohio, Wisconsin","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.779296875,\n 39.9434364619742\n ],\n [\n -93.779296875,\n 48.922499263758255\n ],\n [\n -71.6748046875,\n 48.922499263758255\n ],\n [\n -71.6748046875,\n 39.9434364619742\n ],\n [\n -93.779296875,\n 39.9434364619742\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-08-27","publicationStatus":"PW","scienceBaseUri":"542d098be4b092f17defc4e1","contributors":{"authors":[{"text":"McKenna, James E. Jr.","contributorId":38486,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","affiliations":[],"preferred":false,"id":498188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaeffer, Jeffrey S.","contributorId":19890,"corporation":false,"usgs":true,"family":"Schaeffer","given":"Jeffrey S.","affiliations":[],"preferred":false,"id":498187,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Jana S. 0000-0002-8121-1373 jsstewar@usgs.gov","orcid":"https://orcid.org/0000-0002-8121-1373","contributorId":539,"corporation":false,"usgs":true,"family":"Stewart","given":"Jana","email":"jsstewar@usgs.gov","middleInitial":"S.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498185,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Slattery, Michael T. mslattery@usgs.gov","contributorId":5470,"corporation":false,"usgs":true,"family":"Slattery","given":"Michael","email":"mslattery@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":498186,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70129712,"text":"70129712 - 2015 - Detection of Ichthyophonus by chromogenic in situ hybridization","interactions":[],"lastModifiedDate":"2016-04-26T09:52:45","indexId":"70129712","displayToPublicDate":"2014-10-01T01:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2286,"text":"Journal of Fish Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Detection of Ichthyophonus by chromogenic in situ hybridization","docAbstract":"

Ichthyophonus hoferi (Plehn & Mulsow 1911) is a protistan parasite in the class Mesomycetozoea that infects a large range of marine and freshwater fish (Mendoza, Taylor & Ajello 2002; McVicar 2011). The broad host and geographic range, which includes both fresh and marine waters of the Northern and Southern Hemispheres, combined with a lack of distinguishing morphological characteristics, have prompted speculation that Ichthyophonus-like organisms in multiple species of fish, as well as reptiles, amphibians, birds and invertebrates, may have been incorrectly classified under a single type species I. hoferi (McVicar 2011). At present, only two species,I. hoferi and I. irregularis, are currently recognized within the genus (Rand et al. 2000; Mendoza et al. 2002). Investigations of ribosomal DNA sequence variation have begun to clarify relationships among Ichthyophonus types (Criscione et al. 2002; Rasmussen et al. 2010). Here, we will use the term Ichthyophonus to broadly represent all members of the genus regardless of species/subspecies.

","language":"English","publisher":"Blackwell Science","doi":"10.1111/jfd.12300","usgsCitation":"Conway, C.M., Purcell, M., Elliott, D.G., and Hershberger, P., 2015, Detection of Ichthyophonus by chromogenic in situ hybridization: Journal of Fish Diseases, v. 38, no. 9, p. 853-857, https://doi.org/10.1111/jfd.12300.","productDescription":"5 p.","startPage":"853","endPage":"857","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056548","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":295940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545ded2ce4b0ba8303f92b85","contributors":{"authors":[{"text":"Conway, Carla M. 0000-0002-3851-3616 cmconway@usgs.gov","orcid":"https://orcid.org/0000-0002-3851-3616","contributorId":2946,"corporation":false,"usgs":true,"family":"Conway","given":"Carla","email":"cmconway@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":519908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Purcell, Maureen K. mpurcell@usgs.gov","contributorId":3061,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen K.","email":"mpurcell@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":519910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, Diane G. 0000-0002-4809-6692 dgelliott@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-6692","contributorId":2947,"corporation":false,"usgs":true,"family":"Elliott","given":"Diane","email":"dgelliott@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":519909,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hershberger, Paul K. phershberger@usgs.gov","contributorId":1945,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul K.","email":"phershberger@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":519907,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70142051,"text":"70142051 - 2015 - Rangewide climate vulnerability assessment for threatened Bull Trout","interactions":[],"lastModifiedDate":"2022-10-18T14:25:49.509194","indexId":"70142051","displayToPublicDate":"2014-09-30T09:47:55","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Rangewide climate vulnerability assessment for threatened Bull Trout","docAbstract":"

The bull trout, listed as threatened under the Endangered Species Act, is well adapted to the cold waters of the Northwest. Recent changes in climate have caused winter flooding and warmer summer water temperatures in the region, reducing the cold-water habitats that bull trout depend on. The southernmost bull trout populations, found in Oregon, Washington, Idaho, Montana, and Nevada, are currently restricted to small reserves where the coldest waters still exist. These shrinking habitats have created a severed environment being further split by dams, poor water quality, and invasive species.

The goal of this project was to determine how these factors threaten the species regionally by using predictions of stream temperature to map habitat areas that support juvenile bull trout. Results show that maintaining larger areas of cold water habitat had the greatest, positive impact on bull trout habitat conservation. Other conditions that support bull trout include very cold summer water temperatures, fewer winter floods, and fewer human disturbances (such as the building of dams). Based on these results, specific climate adaptation actions that local managers might consider include prioritizing land and water use to foster colder summer water temperatures, controlling invasive species, increasing connectivity between Bull Trout habitats, and continuing monitoring efforts.

To ensure that these results and habitat maps could be incorporated into management actions, researchers met with stakeholders including the U.S. Fish and Wildlife Service (USFWS), the U.S. Forest Service, and the Burns Paiute Tribe.  As a result, the maps were used in forest planning for the Lolo National Forest in Montana, the Wenatchee River basin, and in the lower Pend Oreille River during the relicensing process for local dam operations. In addition, the recovery plan proposed by the USFWS incorporated these models into detailed analyses of bull trout habitat loss, which managers can use to prioritize actions in their Recovery Unit Implementation Plans. 

","language":"English","publisher":"Northwest Climate Science Center","usgsCitation":"Dunham, J., 2015, Rangewide climate vulnerability assessment for threatened Bull Trout, 47 p.","productDescription":"47 p.","ipdsId":"IP-060209","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":362358,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":298173,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f8c64d2e4b0546c0c397b46/5006f464e4b0abf7ce733f90"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":1808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason B.","email":"jdunham@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":541589,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70127469,"text":"70127469 - 2015 - Threshold-dependent sample sizes for selenium assessment with stream fish tissue","interactions":[],"lastModifiedDate":"2016-12-14T11:58:43","indexId":"70127469","displayToPublicDate":"2014-09-30T09:44:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Threshold-dependent sample sizes for selenium assessment with stream fish tissue","docAbstract":"

Natural resource managers are developing assessments of selenium (Se) contamination in freshwater ecosystems based on fish tissue concentrations. We evaluated the effects of sample size (i.e., number of fish per site) on the probability of correctly detecting mean whole-body Se values above a range of potential management thresholds. We modeled Se concentrations as gamma distributions with shape and scale parameters fitting an empirical mean-to-variance relationship in data from southwestern West Virginia, USA (63 collections, 382 individuals). We used parametric bootstrapping techniques to calculate statistical power as the probability of detecting true mean concentrations up to 3 mg Se/kg above management thresholds ranging from 4 to 8 mg Se/kg. Sample sizes required to achieve 80% power varied as a function of management thresholds and Type I error tolerance (α). Higher thresholds required more samples than lower thresholds because populations were more heterogeneous at higher mean Se levels. For instance, to assess a management threshold of 4 mg Se/kg, a sample of eight fish could detect an increase of approximately 1 mg Se/kg with 80% power (given α = 0.05), but this sample size would be unable to detect such an increase from a management threshold of 8 mg Se/kg with more than a coin-flip probability. Increasing α decreased sample size requirements to detect above-threshold mean Se concentrations with 80% power. For instance, at an α-level of 0.05, an 8-fish sample could detect an increase of approximately 2 units above a threshold of 8 mg Se/kg with 80% power, but when α was relaxed to 0.2, this sample size was more sensitive to increasing mean Se concentrations, allowing detection of an increase of approximately 1.2 units with equivalent power. Combining individuals into 2- and 4-fish composite samples for laboratory analysis did not decrease power because the reduced number of laboratory samples was compensated for by increased precision of composites for estimating mean conditions. However, low sample sizes (<5 fish) did not achieve 80% power to detect near-threshold values (i.e., <1 mg Se/kg) under any scenario we evaluated. This analysis can assist the sampling design and interpretation of Se assessments from fish tissue by accounting for natural variation in stream fish populations.

","language":"English","publisher":"SETAC","publisherLocation":"Pensacola, FL","doi":"10.1002/ieam.1579","usgsCitation":"Hitt, N.P., and Smith, D., 2015, Threshold-dependent sample sizes for selenium assessment with stream fish tissue: Integrated Environmental Assessment and Management, v. 11, no. 1, p. 143-149, https://doi.org/10.1002/ieam.1579.","productDescription":"7 p.","startPage":"143","endPage":"149","ipdsId":"IP-053353","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":472465,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ieam.1579","text":"Publisher Index Page"},{"id":294605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294604,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/ieam.1579"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-09-01","publicationStatus":"PW","scienceBaseUri":"542bb80ee4b0abfb4c8096b3","contributors":{"authors":[{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568 nhitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":4435,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"nhitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":502326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David R.","contributorId":173756,"corporation":false,"usgs":false,"family":"Smith","given":"David R.","affiliations":[],"preferred":false,"id":502325,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70126913,"text":"70126913 - 2015 - Data worth and prediction uncertainty for pesticide transport and fate models in Nebraska and Maryland, United States","interactions":[],"lastModifiedDate":"2015-06-02T11:03:52","indexId":"70126913","displayToPublicDate":"2014-09-25T10:10:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3035,"text":"Pest Management Science","active":true,"publicationSubtype":{"id":10}},"title":"Data worth and prediction uncertainty for pesticide transport and fate models in Nebraska and Maryland, United States","docAbstract":"
\n

BACKGROUND

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Complex environmental models are frequently extrapolated to overcome data limitations in space and time, but quantifying data worth to such models is rarely attempted. The authors determined which field observations most informed the parameters of agricultural system models applied to field sites in Nebraska (NE) and Maryland (MD), and identified parameters and observations that most influenced prediction uncertainty.

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RESULTS

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The standard error of regression of the calibrated models was about the same at both NE (0.59) and MD (0.58), and overall reductions in prediction uncertainties of metolachlor and metolachlor ethane sulfonic acid concentrations were 98.0 and 98.6% respectively. Observation data groups reduced the prediction uncertainty by 55–90% at NE and by 28–96% at MD. Soil hydraulic parameters were well informed by the observed data at both sites, but pesticide and macropore properties had comparatively larger contributions after model calibration.

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CONCLUSIONS

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Although the observed data were sparse, they substantially reduced prediction uncertainty in unsampled regions of pesticide breakthrough curves. Nitrate evidently functioned as a surrogate for soil hydraulic data in well-drained loam soils conducive to conservative transport of nitrogen. Pesticide properties and macropore parameters could most benefit from improved characterization further to reduce model misfit and prediction uncertainty. 

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\n

 

\n

RESULTS: The standard error of regression of the calibrated models was about the same at both NE (0.59) and MD (0.58), and overall reductions in prediction uncertainties of metolachlor and metolachlor ethane sulfonic acid concentrations were 98.0 and 98.6% respectively. Observation data groups reduced the prediction uncertainty by 55–90% at NE and by 28–96% at MD. Soil hydraulic parameters were well informed by the observed data at both sites, but pesticide and macropore properties had comparatively larger contributions after model calibration.

\n

 

\n

CONCLUSIONS: Although the observed data were sparse, they substantially reduced prediction uncertainty in unsampled regions of pesticide breakthrough curves. Nitrate evidently functioned as a surrogate for soil hydraulic data in well-drained loam soils conducive to conservative transport of nitrogen. Pesticide properties and macropore parameters could most benefit from improved characterization further to reduce model misfit and prediction uncertainty.

","language":"English","publisher":"Wiley","doi":"10.1002/ps.3875","usgsCitation":"Nolan, B.T., Malone, R.W., Doherty, J.E., Barbash, J.E., Ma, L., and Shaner, D.L., 2015, Data worth and prediction uncertainty for pesticide transport and fate models in Nebraska and Maryland, United States: Pest Management Science, v. 71, no. 7, p. 972-985, https://doi.org/10.1002/ps.3875.","productDescription":"14 p.","startPage":"972","endPage":"985","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044123","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":294476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294473,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/ps.3875"}],"country":"United States","state":"Maryl;Nebraska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.0535,37.8886 ], [ -104.0535,43.0017 ], [ -75.0492,43.0017 ], [ -75.0492,37.8886 ], [ -104.0535,37.8886 ] ] ] } } ] }","volume":"71","issue":"7","noUsgsAuthors":false,"publicationDate":"2014-09-11","publicationStatus":"PW","scienceBaseUri":"54252087e4b0e641df8a6d92","contributors":{"authors":[{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":502182,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malone, Robert W.","contributorId":10347,"corporation":false,"usgs":false,"family":"Malone","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":502185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, John E.","contributorId":8817,"corporation":false,"usgs":false,"family":"Doherty","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":7046,"text":"Watermark Numerical Computing","active":true,"usgs":false}],"preferred":false,"id":502184,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barbash, Jack E. 0000-0001-9854-8880 jbarbash@usgs.gov","orcid":"https://orcid.org/0000-0001-9854-8880","contributorId":1003,"corporation":false,"usgs":true,"family":"Barbash","given":"Jack","email":"jbarbash@usgs.gov","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":502181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ma, Liwang","contributorId":6751,"corporation":false,"usgs":false,"family":"Ma","given":"Liwang","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":502183,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shaner, Dale L.","contributorId":100766,"corporation":false,"usgs":true,"family":"Shaner","given":"Dale","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":502186,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70108458,"text":"70108458 - 2015 - Understanding heat and groundwater flow through continental flood basalt provinces: insights gained from alternative models of permeability/depth relationships for the Columbia Plateau, USA","interactions":[],"lastModifiedDate":"2019-07-22T12:54:07","indexId":"70108458","displayToPublicDate":"2014-09-19T14:32:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1765,"text":"Geofluids","active":true,"publicationSubtype":{"id":10}},"title":"Understanding heat and groundwater flow through continental flood basalt provinces: insights gained from alternative models of permeability/depth relationships for the Columbia Plateau, USA","docAbstract":"

Heat-flow mapping of the western USA has identified an apparent low-heat-flow anomaly coincident with the Columbia Plateau Regional Aquifer System, a thick sequence of basalt aquifers within the Columbia River Basalt Group (CRBG). A heat and mass transport model (SUTRA) was used to evaluate the potential impact of groundwater flow on heat flow along two different regional groundwater flow paths. Limited in situ permeability (k) data from the CRBG are compatible with a steep permeability decrease (approximately 3.5 orders of magnitude) at 600–900 m depth and approximately 40°C. Numerical simulations incorporating this permeability decrease demonstrate that regional groundwater flow can explain lower-than-expected heat flow in these highly anisotropic (kx/kz ~ 104) continental flood basalts. Simulation results indicate that the abrupt reduction in permeability at approximately 600 m depth results in an equivalently abrupt transition from a shallow region where heat flow is affected by groundwater flow to a deeper region of conduction-dominated heat flow. Most existing heat-flow measurements within the CRBG are from shallower than 600 m depth or near regional groundwater discharge zones, so that heat-flow maps generated using these data are likely influenced by groundwater flow. Substantial k decreases at similar temperatures have also been observed in the volcanic rocks of the adjacent Cascade Range volcanic arc and at Kilauea Volcano, Hawaii, where they result from low-temperature hydrothermal alteration.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geofluids","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/gfl.12095","usgsCitation":"Burns, E., Williams, C.F., Ingebritsen, S.E., Voss, C.I., Spane, F.A., and DeAngelo, J., 2015, Understanding heat and groundwater flow through continental flood basalt provinces: insights gained from alternative models of permeability/depth relationships for the Columbia Plateau, USA: Geofluids, v. 15, no. 1-2, p. 120-138, https://doi.org/10.1111/gfl.12095.","productDescription":"19 p.","startPage":"120","endPage":"138","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053358","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":472466,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gfl.12095","text":"Publisher Index Page"},{"id":294238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294237,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gfl.12095"},{"id":294239,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/gfl.12095/abstract"}],"country":"United States","state":"Idaho;Oregon;Washington","otherGeospatial":"Columbia River Plateau","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122,44.5 ], [ -122,48.5 ], [ -116.5,48.5 ], [ -116.5,44.5 ], [ -122,44.5 ] ] ] } } ] }","volume":"15","issue":"1-2","noUsgsAuthors":false,"publicationDate":"2014-09-19","publicationStatus":"PW","scienceBaseUri":"541d3790e4b0f68901ebd9d4","contributors":{"authors":[{"text":"Burns, Erick R. 0000-0002-1747-0506","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":84802,"corporation":false,"usgs":true,"family":"Burns","given":"Erick R.","affiliations":[{"id":310,"text":"Geology, Minerals, Energy and Geophysics Science Center","active":false,"usgs":true}],"preferred":false,"id":494028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Colin F. 0000-0003-2196-5496 colin@usgs.gov","orcid":"https://orcid.org/0000-0003-2196-5496","contributorId":274,"corporation":false,"usgs":true,"family":"Williams","given":"Colin","email":"colin@usgs.gov","middleInitial":"F.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":494023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":494024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":494025,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spane, Frank A.","contributorId":38910,"corporation":false,"usgs":true,"family":"Spane","given":"Frank","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494027,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeAngelo, Jacob jdeangelo@usgs.gov","contributorId":2376,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":494026,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70127956,"text":"70127956 - 2015 - Development of ten microsatellite loci in the invasive giant African land snail, Achatina (=Lissachatina) fulica Bowdich, 1822","interactions":[],"lastModifiedDate":"2015-02-23T16:15:24","indexId":"70127956","displayToPublicDate":"2014-09-19T09:46:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"title":"Development of ten microsatellite loci in the invasive giant African land snail, Achatina (=Lissachatina) fulica Bowdich, 1822","docAbstract":"

A suite of tetra-nucleotide microsatellite loci were developed for the invasive giant African land snail, Achatina (=Lissachatina) fulica Bowdich, 1822, from Ion Torrent next-generation sequencing data. Ten of the 96 primer sets tested amplified consistently in 30 snails from Miami, Florida, plus 12 individuals representative of their native East Africa, Indian and Pacific Ocean regions. The loci displayed moderate levels of allelic diversity (average 5.6 alleles/locus) and heterozygosity (average 42 %). Levels of genetic diversity were sufficient to produce unique multi-locus genotypes and detect phylogeographic structuring among regional samples. The invasive A. fulica can cause extensive damage to important food crops and natural resources, including native flora and fauna. The loci characterized here will be useful for determining the origins and tracking the spread of invasions, detecting fine-scale spatial structuring and estimating demographic parameters.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Conservation Genetics Resources","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s12686-014-0332-3","usgsCitation":"Morrison, C., Springmann, M.J., Iwanowicz, D., and Wade, C.M., 2015, Development of ten microsatellite loci in the invasive giant African land snail, Achatina (=Lissachatina) fulica Bowdich, 1822: Conservation Genetics Resources, v. 7, no. 1, p. 201-202, https://doi.org/10.1007/s12686-014-0332-3.","productDescription":"2 p.","startPage":"201","endPage":"202","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059479","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":488397,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://nottingham-repository.worktribe.com/output/3189010","text":"External Repository"},{"id":294895,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294888,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s12686-014-0332-3"}],"volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-09-19","publicationStatus":"PW","scienceBaseUri":"542fba9ce4b092f17df61d00","contributors":{"authors":[{"text":"Morrison, Cheryl L. 0000-0001-9425-691X","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":18288,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":502718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Springmann, Marcus J. mspringmann@usgs.gov","contributorId":4372,"corporation":false,"usgs":true,"family":"Springmann","given":"Marcus","email":"mspringmann@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":502716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iwanowicz, Deborah D.","contributorId":39704,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah D.","affiliations":[],"preferred":false,"id":502719,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wade, Christopher M.","contributorId":9186,"corporation":false,"usgs":true,"family":"Wade","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":502717,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70125289,"text":"70125289 - 2015 - Long-term decrease in satellite vegetation indices in response to environmental variables in an iconic desert riparian ecosystem: the Upper San Pedro, Arizona, United States","interactions":[],"lastModifiedDate":"2015-07-01T15:50:43","indexId":"70125289","displayToPublicDate":"2014-09-18T13:43:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Long-term decrease in satellite vegetation indices in response to environmental variables in an iconic desert riparian ecosystem: the Upper San Pedro, Arizona, United States","docAbstract":"

The Upper San Pedro River is one of the few remaining undammed rivers that maintain a vibrant riparian ecosystem in the southwest United States. However, its riparian forest is threatened by diminishing groundwater and surface water inputs, due to either changes in watershed characteristics such as changes in riparian and upland vegetation, or human activities such as regional groundwater pumping. We used satellite vegetation indices to quantify the green leaf density of the groundwater-dependent riparian forest from 1984 to 2012. The river was divided into a southern, upstream (mainly perennial flow) reach and a northern, downstream (mainly intermittent and ephemeral flow) reach. Pre-monsoon (June) Landsat normalized difference vegetation index (NDVI) values showed a 20% drop for the northern reach (P < 0·001) and no net change for the southern reach (P > 0·05). NDVI and enhanced vegetation index values were positively correlated (P < 0·05) with river flows, which decreased over the study period in the northern reach, and negatively correlated (P < 0·05) with air temperatures in both reaches, which have increased by 1·4 °C from 1932 to 2012. NDVI in the uplands around the river did not increase from 1984 to 2012, suggesting that increased evapotranspiration in the uplands was not a factor in reducing river flows. Climate change, regional groundwater pumping, changes in the intensity of monsoon rain events and lack of overbank flooding are feasible explanations for deterioration of the riparian forest in the northern reach.

","language":"English","publisher":"John Wiley & Sons Ltd.","doi":"10.1002/eco.1529","usgsCitation":"Nguyen, U., Glenn, E.P., Nagler, P.L., and Scott, R.L., 2015, Long-term decrease in satellite vegetation indices in response to environmental variables in an iconic desert riparian ecosystem: the Upper San Pedro, Arizona, United States: Ecohydrology, v. 8, no. 4, p. 610-625, https://doi.org/10.1002/eco.1529.","productDescription":"16 p.","startPage":"610","endPage":"625","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052717","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":294183,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294181,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/eco.1529"}],"country":"United States","state":"Arizona","otherGeospatial":"Upper San Pedro River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -110.433333,31.25 ], [ -110.433333,32.166667 ], [ -109.816667,32.166667 ], [ -109.816667,31.25 ], [ -110.433333,31.25 ] ] ] } } ] }","volume":"8","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"541be60de4b0e96537dda074","contributors":{"authors":[{"text":"Nguyen, Uyen","contributorId":71863,"corporation":false,"usgs":false,"family":"Nguyen","given":"Uyen","email":"","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":501145,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":501143,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":501142,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scott, Russell L.","contributorId":39875,"corporation":false,"usgs":false,"family":"Scott","given":"Russell","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":501144,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70125306,"text":"70125306 - 2015 - Forest Ecosystem respiration estimated from eddy covariance and chamber measurements under high turbulence and substantial tree mortality from bark beetles","interactions":[],"lastModifiedDate":"2015-02-02T14:31:30","indexId":"70125306","displayToPublicDate":"2014-09-18T10:49:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Forest Ecosystem respiration estimated from eddy covariance and chamber measurements under high turbulence and substantial tree mortality from bark beetles","docAbstract":"

Eddy covariance nighttime fluxes are uncertain due to potential measurement biases. Many studies report eddy covariance nighttime flux lower than flux from extrapolated chamber measurements, despite corrections for low turbulence. We compared eddy covariance and chamber estimates of ecosystem respiration at the GLEES Ameriflux site over seven growing seasons under high turbulence (summer night mean friction velocity (u*) = 0.7 m s−1), during which bark beetles killed or infested 85% of the aboveground respiring biomass. Chamber-based estimates of ecosystem respiration during the growth season, developed from foliage, wood and soil CO2 efflux measurements, declined 35% after 85% of the forest basal area had been killed or impaired by bark beetles (from 7.1 ±0.22 μmol m−2 s−1 in 2005 to 4.6 ±0.16 μmol m−2 s−1 in 2011). Soil efflux remained at ~3.3 μmol m−2 s−1 throughout the mortality, while the loss of live wood and foliage and their respiration drove the decline of the chamber estimate. Eddy covariance estimates of fluxes at night remained constant over the same period, ~3.0 μmol m−2 s−1 for both 2005 (intact forest) and 2011 (85% basal area killed or impaired). Eddy covariance fluxes were lower than chamber estimates of ecosystem respiration (60% lower in 2005, and 32% in 2011), but the mean night estimates from the two techniques were correlated within a year (r2 from 0.18-0.60). The difference between the two techniques was not the result of inadequate turbulence, because the results were robust to a u* filter of > 0.7 m s−1. The decline in the average seasonal difference between the two techniques was strongly correlated with overstory leaf area (r2=0.92). The discrepancy between methods of respiration estimation should be resolved to have confidence in ecosystem carbon flux estimates.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Global Change Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley-Blackwell","publisherLocation":"Oxford, United Kingdom","doi":"10.1111/gcb.12731","usgsCitation":"Speckman, H.N., Frank, J.M., Bradford, J.B., Miles, B.L., Massman, W.J., Parton, W.J., and Ryan, M., 2015, Forest Ecosystem respiration estimated from eddy covariance and chamber measurements under high turbulence and substantial tree mortality from bark beetles: Global Change Biology, v. 21, no. 1, p. 708-721, https://doi.org/10.1111/gcb.12731.","productDescription":"14 p.","startPage":"708","endPage":"721","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058138","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":294128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293880,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gcb.12731"}],"country":"United States","state":"Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.2938,41.3102 ], [ -106.2938,41.3858 ], [ -106.181,41.3858 ], [ -106.181,41.3102 ], [ -106.2938,41.3102 ] ] ] } } ] }","volume":"21","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-10-18","publicationStatus":"PW","scienceBaseUri":"541be606e4b0e96537dda049","contributors":{"authors":[{"text":"Speckman, Heather N.","contributorId":65777,"corporation":false,"usgs":true,"family":"Speckman","given":"Heather","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":501206,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frank, John M.","contributorId":11969,"corporation":false,"usgs":true,"family":"Frank","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":501203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":501202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miles, Brianna L.","contributorId":100765,"corporation":false,"usgs":true,"family":"Miles","given":"Brianna","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":501207,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Massman, William J.","contributorId":24707,"corporation":false,"usgs":true,"family":"Massman","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":501204,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parton, William J.","contributorId":55545,"corporation":false,"usgs":true,"family":"Parton","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":501205,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ryan, Michael G.","contributorId":101580,"corporation":false,"usgs":true,"family":"Ryan","given":"Michael G.","affiliations":[],"preferred":false,"id":501208,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70125710,"text":"70125710 - 2015 - MODFLOW-based coupled surface water routing and groundwater-flow simulation","interactions":[],"lastModifiedDate":"2015-05-05T11:34:56","indexId":"70125710","displayToPublicDate":"2014-09-17T15:23:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"MODFLOW-based coupled surface water routing and groundwater-flow simulation","docAbstract":"

In this paper, we present a flexible approach for simulating one- and two-dimensional routing of surface water using a numerical surface water routing (SWR) code implicitly coupled to the groundwater-flow process in MODFLOW. Surface water routing in SWR can be simulated using a diffusive-wave approximation of the Saint-Venant equations and/or a simplified level-pool approach. SWR can account for surface water flow controlled by backwater conditions caused by small water-surface gradients or surface water control structures. A number of typical surface water control structures, such as culverts, weirs, and gates, can be represented, and it is possible to implement operational rules to manage surface water stages and streamflow. The nonlinear system of surface water flow equations formulated in SWR is solved by using Newton methods and direct or iterative solvers. SWR was tested by simulating the (1) Lal axisymmetric overland flow, (2) V-catchment, and (3) modified Pinder-Sauer problems. Simulated results for these problems compare well with other published results and indicate that SWR provides accurate results for surface water-only and coupled surface water/groundwater problems. Results for an application of SWR and MODFLOW to the Snapper Creek area of Miami-Dade County, Florida, USA are also presented and demonstrate the value of coupled surface water and groundwater simulation in managed, low-relief coastal settings.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Groundwater","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/gwat.12216","usgsCitation":"Hughes, J.D., Langevin, C.D., and White, J., 2015, MODFLOW-based coupled surface water routing and groundwater-flow simulation: Groundwater, v. 53, no. 3, p. 452-463, https://doi.org/10.1111/gwat.12216.","productDescription":"12 p.","startPage":"452","endPage":"463","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053378","costCenters":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"links":[{"id":294073,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294069,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gwat.12216"}],"volume":"53","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-06-05","publicationStatus":"PW","scienceBaseUri":"541a9491e4b01571b3d4cc5a","contributors":{"authors":[{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":501635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":501634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Jeremy T. jwhite@usgs.gov","contributorId":3930,"corporation":false,"usgs":true,"family":"White","given":"Jeremy T.","email":"jwhite@usgs.gov","affiliations":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":false,"id":501636,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70125432,"text":"70125432 - 2015 - How have fisheries affected parasite communities?","interactions":[],"lastModifiedDate":"2015-02-09T15:27:36","indexId":"70125432","displayToPublicDate":"2014-09-17T13:47:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3011,"text":"Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"How have fisheries affected parasite communities?","docAbstract":"

To understand how fisheries affect parasites, we conducted a meta-analysis of studies that contrasted parasite assemblages in fished and unfished areas. Parasite diversity was lower in hosts from fished areas. Larger hosts had a greater abundance of parasites, suggesting that fishing might reduce the abundance of parasites by selectively removing the largest, most heavily parasitized individuals. After controlling for size, the effect of fishing on parasite abundance varied according to whether the host was fished and the parasite's life cycle. Parasites of unfished hosts were more likely to increase in abundance in response to fishing than were parasites of fished hosts, possibly due to compensatory increases in the abundance of unfished hosts. While complex life cycle parasites tended to decline in abundance in response to fishing, directly transmitted parasites tended to increase. Among complex life cycle parasites, those with fished hosts tended to decline in abundance in response to fishing, while those with unfished hosts tended to increase. However, among directly transmitted parasites, responses did not differ between parasites with and without fished hosts. This work suggests that parasite assemblages are likely to change substantially in composition in increasingly fished ecosystems, and that parasite life history and fishing status of the host are important in predicting the response of individual parasite species or groups to fishing.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Parasitology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Cambridge University Press","doi":"10.1017/S003118201400002X","usgsCitation":"Wood, C., and Lafferty, K.D., 2015, How have fisheries affected parasite communities?: Parasitology, v. 142, no. 1, p. 134-144, https://doi.org/10.1017/S003118201400002X.","productDescription":"11 p.","startPage":"134","endPage":"144","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054355","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":294061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293995,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1017/S003118201400002X"}],"volume":"142","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-03-03","publicationStatus":"PW","scienceBaseUri":"541a948ee4b01571b3d4cc39","contributors":{"authors":[{"text":"Wood, Chelsea L.","contributorId":36866,"corporation":false,"usgs":true,"family":"Wood","given":"Chelsea L.","affiliations":[],"preferred":false,"id":501434,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":501433,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70125494,"text":"70125494 - 2015 - Demography of the Pacific walrus (Odobenus rosmarus divergens): 1974-2006","interactions":[],"lastModifiedDate":"2015-01-05T11:05:29","indexId":"70125494","displayToPublicDate":"2014-09-17T09:47:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2671,"text":"Marine Mammal Science","active":true,"publicationSubtype":{"id":10}},"title":"Demography of the Pacific walrus (Odobenus rosmarus divergens): 1974-2006","docAbstract":"

Global climate change may fundamentally alter population dynamics of many species for which baseline population parameter estimates are imprecise or lacking. Historically, the Pacific walrus is thought to have been limited by harvest, but it may become limited by global warming-induced reductions in sea ice. Loss of sea ice, on which walruses rest between foraging bouts, may reduce access to food, thus lowering vital rates. Rigorous walrus survival rate estimates do not exist, and other population parameter estimates are out of date or have well-documented bias and imprecision. To provide useful population parameter estimates we developed a Bayesian, hidden process demographic model of walrus population dynamics from 1974 through 2006 that combined annual age-specific harvest estimates with five population size estimates, six standing age structure estimates, and two reproductive rate estimates. Median density independent natural survival was high for juveniles (0.97) and adults (0.99), and annual density dependent vital rates rose from 0.06 to 0.11 for reproduction, 0.31 to 0.59 for survival of neonatal calves, and 0.39 to 0.85 for survival of older calves, concomitant with a population decline. This integrated population model provides a baseline for estimating changing population dynamics resulting from changing harvests or sea ice.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Mammal Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/mms.12156","usgsCitation":"Taylor, R.L., and Udevitz, M.S., 2015, Demography of the Pacific walrus (Odobenus rosmarus divergens): 1974-2006: Marine Mammal Science, v. 31, no. 1, p. 231-254, https://doi.org/10.1111/mms.12156.","productDescription":"24 p.","startPage":"231","endPage":"254","numberOfPages":"24","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050957","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":294017,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/mms.12156"},{"id":294021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-09-05","publicationStatus":"PW","scienceBaseUri":"541a948be4b01571b3d4cc17","chorus":{"doi":"10.1111/mms.12156","url":"http://dx.doi.org/10.1111/mms.12156","publisher":"Wiley-Blackwell","authors":"Taylor Rebecca L., Udevitz Mark S.","journalName":"Marine Mammal Science","publicationDate":"9/5/2014","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":501516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":501515,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}